The Experts below are selected from a list of 82293 Experts worldwide ranked by ideXlab platform
Li Layuan - One of the best experts on this subject based on the ideXlab platform.
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Cross-layer optimization policy for QoS scheduling in Computational Grid
Journal of Network and Computer Applications, 2008Co-Authors: Li Chunlin, Li LayuanAbstract:This paper presents a cross-layer quality of service (QoS) optimization policy for Computational Grid. Efficient QoS management is critical for Computational Grid to meet heterogeneity and dynamics of resources and users' requirements. There are different QoS metrics at different layers of Computational Grid. To improve perceived QoS by end users over Computational Grid, QoS supports can be addressed in different layers, including application layer, collective layer, fabric layer and so forth. The paper tackles cross-layer Grid QoS optimization as optimization decomposition, each layer corresponds to a decomposed subproblem. The proposed policy produces an optimal set of Grid resources, service compositions and user's payments at the fabric layer, collective layer and application layer respectively to maximize global Grid QoS. The cross-layer optimization problem decomposes into three subproblems: Grid resource allocation problem, service composing and user satisfaction degree maximization problem, all of which interact through the optimal variables for capacities of Grid resources and service demand. In order to coordinate the subproblems, cross-layer QoS feedback mechanism is established to ensure different layer interactions. The simulations are conducted to validate the efficiency of the proposed policy.
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multi economic agent interaction for optimizing the aggregate utility of Grid users in Computational Grid
Applied Intelligence, 2006Co-Authors: Li Chunlin, Li LayuanAbstract:This paper investigates the interactions between agents representing Grid users and the providers of Grid resources to maximize the aggregate utilities of all Grid users in Computational Grid. It proposes a price-based resource allocation model to achieve maximized utility of Grid users and providers in Computational Grid. Existing distributed resource allocation schemes assume the resource provider to be capable of measuring user's resource demand, calculating and communicating price, none of which actually exists in reality. This paper addresses these challenges as follows. First, the Grid user utility is defined as a function of the Grid user's the resource units allocated. We formalize resource allocation using nonlinear optimization theory, which incorporates both Grid resource capacity constraint and the job complete times. An optimal solution maximizes the aggregate utilities of all Grid users. Second, this paper proposes a new optimization-based Grid resource pricing algorithm for allocating resources to Grid users while maximizing the revenue of Grid providers. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme.
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a distributed utility based two level market solution for optimal resource scheduling in Computational Grid
Parallel Computing, 2005Co-Authors: Li Chunlin, Li LayuanAbstract:This paper investigates the interactions between agents representing users, services and resources to solve resource scheduling optimization in Computational Grid. In order to reduce the Computational complexity, we further decompose the Grid resource allocation optimization into subproblems: Grid user agent-Grid service agent in service market and Grid service agent-Grid resource agent in resource market. Two-level market converges to its optimal points; a globally optimal point is achieved. Total user benefit of the Computational Grid is maximized when the equilibrium prices are obtained through the service market level optimization and resource market level optimization. It demonstrates a practical approach to market responsive resource pricing that can benefit Grid providers and users alike. The paper presents two-level market Grid resource pricing that is an iterative algorithm used to perform optimal resource allocation. The experiment shows that two-level market based resource pricing scheme outperforms one level market scheme in terms of task completion time and resource allocation efficiency.
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agent framework to support the Computational Grid
Journal of Systems and Software, 2004Co-Authors: Li Chunlin, Li LayuanAbstract:This paper presents an agent-based Computational Grid (ACG), which applies the concept of Computational Grid to agents. The ACG system is to implement a uniform higher-level management of the computing resources and services on the Grid, and provide users with a consistent and transparent interface for accessing such services. All entities in the Grid environment including computing resources and services can be represented as agents. Each entity is registered with a Grid service manager. Service requestor agent locates a specific Grid service by submitting requests to the Grid service manager with descriptions of required services. XML is used to describe both Grid service descriptions and service requestor agent's queries. An ACG Grid service can be a service agent that provides the actual Grid service to the other Grid member. In this paper, firstly, the conceptual model about ACG Grid is described, and then the design and implementation are given. Finally, some conclusions are given.
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Integrate software agents and CORBA in Computational Grid
Computer Standards & Interfaces, 2003Co-Authors: Li Chunlin, Li LayuanAbstract:This paper presents an Agent-based Computational Grid (ACG), which applies the concept of CORBA and agent to Computational Grid. The ACG system is used to implement a uniform higher level management of the computing resources and services on the Grid, and provide users with a consistent and transparent interface for accessing such services. In ACG Grid, Grid services are implemented by CORBA or by Grid agent. Grid agents and CORBA objects will interact with each other to achieve user's service request. Our solution is the creation of a bridge between the CORBA and Grid agents The solution provides with the opportunity of considering an agent as a CORBA service and accessing CORBA services even from a Grid agent. Thus, in AGC Grid, existing legacy systems can be easily exploited as Grid services. In this paper, firstly, the features of ACG Grid are described, and then the design and implementation are given. Finally, some conclusions are given.
Deo Prakash Vidyarthi - One of the best experts on this subject based on the ideXlab platform.
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A model for resource management in Computational Grid using sequential auction and bargaining procurement
Cluster Computing, 2018Co-Authors: Achal Kaushik, Deo Prakash VidyarthiAbstract:Resources in a Computational Grid system fall under the purview of different administrative domains of varying policies for their usages. Commercial Grid offers their services (resources) on use-and-pay basis. Resource management in Computational Grid, offers a market place for the two prominent Grid market players i.e. resource provider and resource consumer. It has been observed that, in the Grid, the request for the resources may not be uniform throughout. It fluctuates from very high demand at peak time to low or negligible at off-peak time. This information may be used to fetch the resource utilization and cost benefits out of the Grid. The provider would prefer to charge extra for its resources at peak time, whereas users may shift their resources usage preference to off-peak time. This work proposes a model in which the resource provider and consumer play a non-cooperative game at different time-zones and act independently to choose their actions. Some characteristic parameters such as cost, execution time and reliability have been considered to facilitate the job execution. Based on the outcome of the game, the Grid cluster offering maximum reliability within the desired execution time and/or cost for the job execution. The model has been simulated for performance evaluation with quite encouraging results.
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Security Driven Scheduling Model for Computational Grid Using NSGA-II
Journal of Grid Computing, 2013Co-Authors: Rekha Kashyap, Deo Prakash VidyarthiAbstract:Number of software applications demands various levels of security at the time of scheduling in Computational Grid. Grid may offer these securities but may result in the performance degradation due to overhead in offering the desired security. Scheduling performance in a Grid is affected by the heterogeneities of security and Computational power of resources. Customized Genetic Algorithms have been effectively used for solving complex optimization problems (NP Hard) and various heuristics have been suggested for solving Multi-objective optimization problems. In this paper a security driven, elitist non-dominated sorting genetic algorithm, Optimal Security with Optimal Overhead Scheduling (OSO_2S), based on NSGA-II, is proposed. The model considers dual objectives of minimizing the security overhead and maximizing the total security achieved. Simulation results exhibit that the proposed algorithm delivers improved makespan and lesser security overhead in comparison to other such algorithms viz. MinMin, MaxMin, SPMinMin, SPMaxMin and SDSG.
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A novel scheduling model for Computational Grid using quantum genetic algorithm
The Journal of Supercomputing, 2013Co-Authors: Shiv Prakash, Deo Prakash VidyarthiAbstract:The Computational Grid (CG) provides a wide distributed platform for high end computing intensive applications. Scheduling on Computational Grid is known to be NP-Hard problem and requires an efficient solution. Recently, quantum inspired computing has been introduced in the literature to solve such a complex combinatorial optimization problem efficiently. Combination of Genetic Algorithm (GA) and quantum concept evolves a new meta-heuristic technique known as Quantum Genetic Algorithms (QGA). QGA is a search procedure based on evolutionary computation and Quantum Computing (QC). This paper proposes a novel technique of scheduling in Computational Grid using QGA. The work simulates the model to study its performance. It also makes a comparative study with a GA-based scheduling model. Simulation results reveal the effectiveness of the model.
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load balancing in Computational Grid using genetic algorithm
Advances in Computers, 2012Co-Authors: Shiv Prakash, Deo Prakash VidyarthiAbstract:Computational Grid is an aggregation of geographically distributed network of computing nodes specially de- signed for compute intensive applications. The diversity of Computational Grid helps in resource utilization in order to support execution of all types of jobs; fine grain as well as coarse grain. It is observed that, over the period of time in the course of job execution, Grid becomes highly imbalance resulting in performance degradation. It warrants balancing the load amongst the Grid nodes. In absence of centralized information in a system such as Grid, load balancing becomes a complex problem. Genetic Algorithm, a search procedure based on evolutionary computation, is able to solve a class of complex optimization problems. A model based on genetic algorithm is proposed, in this work, to achieve better load balancing in Computational Grid. To study the performance of the proposed model, experiments have been conducted by simulating the model. Experi- mental results reveal the effectiveness of the proposed model.
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observations on effect of ipc in ga based scheduling on Computational Grid
IEEE International Conference on High Performance Computing Data and Analytics, 2012Co-Authors: Deo Prakash Vidyarthi, Shiv PrakashAbstract:Computational Grid CG provides a wide distributed platform for high end compute intensive applications. Inter Process Communication IPC affects the performance of a scheduling algorithm drastically. Genetic Algorithms GA, a search procedure based on the evolutionary computation, is able to solve a class of complex optimization problems. This paper proposes a GA based scheduling model observing the effect of IPC on the performance of scheduling in Computational Grid. The proposed model studies the effects of Inter Process Communication IPC, processing rate and arrival rate. Simulation experiment, to evaluate the performance of the proposed algorithm is conducted and results reveal the effectiveness of the model.
Li Chunlin - One of the best experts on this subject based on the ideXlab platform.
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Cross-layer optimization policy for QoS scheduling in Computational Grid
Journal of Network and Computer Applications, 2008Co-Authors: Li Chunlin, Li LayuanAbstract:This paper presents a cross-layer quality of service (QoS) optimization policy for Computational Grid. Efficient QoS management is critical for Computational Grid to meet heterogeneity and dynamics of resources and users' requirements. There are different QoS metrics at different layers of Computational Grid. To improve perceived QoS by end users over Computational Grid, QoS supports can be addressed in different layers, including application layer, collective layer, fabric layer and so forth. The paper tackles cross-layer Grid QoS optimization as optimization decomposition, each layer corresponds to a decomposed subproblem. The proposed policy produces an optimal set of Grid resources, service compositions and user's payments at the fabric layer, collective layer and application layer respectively to maximize global Grid QoS. The cross-layer optimization problem decomposes into three subproblems: Grid resource allocation problem, service composing and user satisfaction degree maximization problem, all of which interact through the optimal variables for capacities of Grid resources and service demand. In order to coordinate the subproblems, cross-layer QoS feedback mechanism is established to ensure different layer interactions. The simulations are conducted to validate the efficiency of the proposed policy.
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multi economic agent interaction for optimizing the aggregate utility of Grid users in Computational Grid
Applied Intelligence, 2006Co-Authors: Li Chunlin, Li LayuanAbstract:This paper investigates the interactions between agents representing Grid users and the providers of Grid resources to maximize the aggregate utilities of all Grid users in Computational Grid. It proposes a price-based resource allocation model to achieve maximized utility of Grid users and providers in Computational Grid. Existing distributed resource allocation schemes assume the resource provider to be capable of measuring user's resource demand, calculating and communicating price, none of which actually exists in reality. This paper addresses these challenges as follows. First, the Grid user utility is defined as a function of the Grid user's the resource units allocated. We formalize resource allocation using nonlinear optimization theory, which incorporates both Grid resource capacity constraint and the job complete times. An optimal solution maximizes the aggregate utilities of all Grid users. Second, this paper proposes a new optimization-based Grid resource pricing algorithm for allocating resources to Grid users while maximizing the revenue of Grid providers. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme.
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a distributed utility based two level market solution for optimal resource scheduling in Computational Grid
Parallel Computing, 2005Co-Authors: Li Chunlin, Li LayuanAbstract:This paper investigates the interactions between agents representing users, services and resources to solve resource scheduling optimization in Computational Grid. In order to reduce the Computational complexity, we further decompose the Grid resource allocation optimization into subproblems: Grid user agent-Grid service agent in service market and Grid service agent-Grid resource agent in resource market. Two-level market converges to its optimal points; a globally optimal point is achieved. Total user benefit of the Computational Grid is maximized when the equilibrium prices are obtained through the service market level optimization and resource market level optimization. It demonstrates a practical approach to market responsive resource pricing that can benefit Grid providers and users alike. The paper presents two-level market Grid resource pricing that is an iterative algorithm used to perform optimal resource allocation. The experiment shows that two-level market based resource pricing scheme outperforms one level market scheme in terms of task completion time and resource allocation efficiency.
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agent framework to support the Computational Grid
Journal of Systems and Software, 2004Co-Authors: Li Chunlin, Li LayuanAbstract:This paper presents an agent-based Computational Grid (ACG), which applies the concept of Computational Grid to agents. The ACG system is to implement a uniform higher-level management of the computing resources and services on the Grid, and provide users with a consistent and transparent interface for accessing such services. All entities in the Grid environment including computing resources and services can be represented as agents. Each entity is registered with a Grid service manager. Service requestor agent locates a specific Grid service by submitting requests to the Grid service manager with descriptions of required services. XML is used to describe both Grid service descriptions and service requestor agent's queries. An ACG Grid service can be a service agent that provides the actual Grid service to the other Grid member. In this paper, firstly, the conceptual model about ACG Grid is described, and then the design and implementation are given. Finally, some conclusions are given.
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Integrate software agents and CORBA in Computational Grid
Computer Standards & Interfaces, 2003Co-Authors: Li Chunlin, Li LayuanAbstract:This paper presents an Agent-based Computational Grid (ACG), which applies the concept of CORBA and agent to Computational Grid. The ACG system is used to implement a uniform higher level management of the computing resources and services on the Grid, and provide users with a consistent and transparent interface for accessing such services. In ACG Grid, Grid services are implemented by CORBA or by Grid agent. Grid agents and CORBA objects will interact with each other to achieve user's service request. Our solution is the creation of a bridge between the CORBA and Grid agents The solution provides with the opportunity of considering an agent as a CORBA service and accessing CORBA services even from a Grid agent. Thus, in AGC Grid, existing legacy systems can be easily exploited as Grid services. In this paper, firstly, the features of ACG Grid are described, and then the design and implementation are given. Finally, some conclusions are given.
Thomas Witzel - One of the best experts on this subject based on the ideXlab platform.
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using top c and ampic to port large parallel applications to the Computational Grid
Future Generation Computer Systems, 2003Co-Authors: Gene Cooperman, Henri Casanova, Jim Hayes, Thomas WitzelAbstract:Porting large parallel applications to new and various distributed computing platforms is a challenging task from a software engineering perspective. The primary aim of this paper is to demonstrate how the development time to port very large applications to the Computational Grid can be significantly reduced. TOP-C and AMPIC are software packages that have each seen successful applications in their respective domains of parallel computing and process creation/communication over the Computational Grid. We combined the two packages in 1 man-week, thereby leveraging several man-years of previous independent software development. As a real world test case, the 1,000,000 line Geant4 sequential application was then deployed over the Computational Grid in 3 man-weeks by using TOP-C/AMPIC. The cluster parallelization of Geant4 using TOP-C is now included as part of the Geant4 4.1 distribution, and the integration of TOP-C/AMPIC and the Globus protocols will additionally enable the use of the fundamental Grid middleware services in the future.
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using top c and ampic to port large parallel applications to the Computational Grid
Cluster Computing and the Grid, 2002Co-Authors: Gene Cooperman, Henri Casanova, Jim Hayes, Thomas WitzelAbstract:Porting large applications to distributed computing platforms is a challenging task from a software engineering perspective. The Computational Grid has gained tremendous popularity as it aggregates unprecedented amounts of compute and storage resources by means of increasingly high performance network technology. The primary aim of this paper is to demonstrate how the development time to port very large applications to this environment can be significantly reduced. TOP-C and AMPIC are software packages that have each seen successful application in their respective domains of parallel computing and process creation/communication. We combine them to implement and deploy a master-worker model of parallel computing over the Computational Grid. To demonstrate the benefit of our approach, we ported the 1,000,000 line Geant4 sequential code in three man-weeks by using our TOP-C/AMPIC integration. This paper evaluates the benefits of our approach from a software engineering perspective, and presents experimental results obtained with the new implementation of Geant4 on a Grid testbed.
Sergey Zhuk - One of the best experts on this subject based on the ideXlab platform.
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two level job scheduling strategies for a Computational Grid
Lecture Notes in Computer Science, 2006Co-Authors: Andrei Tchernykh, Juan M Ramirez, Arutyun Avetisyan, Nikolai N Kuzjurin, Dmitri Grushin, Sergey ZhukAbstract:We address parallel jobs scheduling problem for Computational Grid systems. We concentrate on two-level hierarchy scheduling: at the first level broker allocates Computational jobs to parallel computers. At the second level each computer generates schedules of the parallel jobs assigned to it by its own local scheduler. Selection, allocation strategies, and efficiency of proposed hierarchical scheduling algorithms are discussed.